New Research on an Old Collection: Studies of the Philippine Expedition (“Guthe”) Collection of the Museum of Anthropology, University of Michigan

This article introduces recent studies on an important collection of Southeast Asian archaeological materials curated by the Asian Division of the University of Michigan Museum of Anthropology. The Philippine Expedition or Guthe Collection derives from archaeological research conducted at more than 500 sites in the southern and central Philippines in the early part of the last century—from 1922 to 1925. The collection consists of some 13,000 objects from some of the earliest systematic archaeological research in Southeast Asia. For more than 80 years, scholars from the Philippines, China, Japan, Europe, and North America have visited the collection to study the materials and ask new questions about the Southeast Asian past. The articles here continue this trajectory by presenting recent research on early modern trade in blue-on-white porcelains; technological style and the classification of large stoneware dragon jars; the cultural context of cranial deformation; and a sourcing study of indigenous earthenware ceramics using instrumental neutron activation. In this article, I provide some background on the Philippine Expedition and the remarkable museum collection that it generated, as well as some of this research, which continues to mine new knowledge from this nearly century-old museum collection

Colonial Collecting and Display: Encounters with Material Culture from the Andaman and Nicobar Islands . Claire Wintle. Oxford : Bergahn Books , 2013 . 264 PP.

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/108699/1/muan12062.pd

Large Deviations Performance of Consensus+Innovations Distributed Detection with Non-Gaussian Observations

We establish the large deviations asymptotic performance (error exponent) of consensus+innovations distributed detection over random networks with generic (non-Gaussian) sensor observations. At each time instant, sensors 1) combine theirs with the decision variables of their neighbors (consensus) and 2) assimilate their new observations (innovations). This paper shows for general non-Gaussian distributions that consensus+innovations distributed detection exhibits a phase transition behavior with respect to the network degree of connectivity. Above a threshold, distributed is as good as centralized, with the same optimal asymptotic detection performance, but, below the threshold, distributed detection is suboptimal with respect to centralized detection. We determine this threshold and quantify the performance loss below threshold. Finally, we show the dependence of the threshold and performance on the distribution of the observations: distributed detectors over the same random network, but with different observations' distributions, for example, Gaussian, Laplace, or quantized, may have different asymptotic performance, even when the corresponding centralized detectors have the same asymptotic performance.Comment: 30 pages, journal, submitted Nov 17, 2011; revised Apr 3, 201

Consensus and Products of Random Stochastic Matrices: Exact Rate for Convergence in Probability

Distributed consensus and other linear systems with system stochastic matrices $W_k$ emerge in various settings, like opinion formation in social networks, rendezvous of robots, and distributed inference in sensor networks. The matrices $W_k$ are often random, due to, e.g., random packet dropouts in wireless sensor networks. Key in analyzing the performance of such systems is studying convergence of matrix products $W_kW_{k-1}... W_1$. In this paper, we find the exact exponential rate $I$ for the convergence in probability of the product of such matrices when time $k$ grows large, under the assumption that the $W_k$'s are symmetric and independent identically distributed in time. Further, for commonly used random models like with gossip and link failure, we show that the rate $I$ is found by solving a min-cut problem and, hence, easily computable. Finally, we apply our results to optimally allocate the sensors' transmission power in consensus+innovations distributed detection

Distributed Detection over Random Networks: Large Deviations Performance Analysis

We study the large deviations performance, i.e., the exponential decay rate of the error probability, of distributed detection algorithms over random networks. At each time step $k$ each sensor: 1) averages its decision variable with the neighbors' decision variables; and 2) accounts on-the-fly for its new observation. We show that distributed detection exhibits a "phase change" behavior. When the rate of network information flow (the speed of averaging) is above a threshold, then distributed detection is asymptotically equivalent to the optimal centralized detection, i.e., the exponential decay rate of the error probability for distributed detection equals the Chernoff information. When the rate of information flow is below a threshold, distributed detection achieves only a fraction of the Chernoff information rate; we quantify this achievable rate as a function of the network rate of information flow. Simulation examples demonstrate our theoretical findings on the behavior of distributed detection over random networks.Comment: 30 pages, journal, submitted on December 3rd, 201

Large-Scale Distribution of the European Seahorses (Hippocampus Rafinesque, 1810): A Systematic Review

Human pressures on marine ecosystems have caused extensive degradation of marine habitats and several local extinctions. Overexploitation and destructive fishing practices are responsible for biodiversity loss in many coastal ecosystems. The definition of conservation programs in marine fish requires comprehensive knowledge on large-scale geographical distribution, while considering distribution/abundance patterns in relation to key environmental variables. Due to their life-cycle traits, the two European seahorses (Hippocampus guttulatus and H. hippocampus), as with other congeneric species, are particularly sensitive to the effects of anthropogenic activities and habitat changes. However, information on the ecological distribution of these two species is scattered, patchy, and mainly focused on small-scale studies. In this paper, we followed an international standard protocol for systematic reviews (the PRISMA protocol) to provide a detailed assessment of the two species’ geographical distribution in relation to the environmental characteristics. According to the 134 analyzed studies, Hippocampus guttulatus is more common in confined areas, while H. hippocampus is found in marine shelf waters. With several interspecific differences, seagrasses were the most used holdfasts of both species. The EUNIS codes (European nature information system) referring to a specific and unique habitat were discussed as a potential tool for defining the ecological distribution of the two species. The obtained results and their future implementation could help plan conservation actions